Pathology

Classification of colorectal tissue images from high throughput tissue microarrays by ensemble deep learning methods.

Tissue microarray (TMA) core images are a treasure trove for artificial intelligence applications. However, a common problem of TMAs is multiple sectioning, which can change the content of the intended tissue core and requires re-labelling. Here, we investigate different ensemble methods for colorectal tissue classification using high-throughput TMAs. Hematoxylin and Eosin (H&E) core images of 0.6...

Involvement of Machine Learning Tools in Healthcare Decision Making.

In the present day, there are many diseases which need to be identified at their early stages to start relevant treatments. If not, they could be uncurable and deadly. Due to this reason, there is a need of analysing complex medical data, medical reports, and medical images at a lesser time but with greater accuracy. There are even some instances where certain abnormalities cannot be directly reco...

Artificial intelligence in dermatopathology: Diagnosis, education, and research.

Artificial intelligence (AI) utilizes computer algorithms to carry out tasks with human-like intelligence. Convolutional neural networks, a type of de...

Radiomics to better characterize small renal masses.

PURPOSE: Radiomics is a specific field of medical research that uses programmable recognition tools to extract objective information from standard ima...

Identifying metastatic ability of prostate cancer cell lines using native fluorescence spectroscopy and machine learning methods.

Metastasis is the leading cause of mortalities in cancer patients due to the spreading of cancer cells to various organs. Detecting cancer and identif...

Intracorporeal anastomosis in right hemicolectomy for colon cancer: short-term outcomes with the DaVinci Xi robot.

Intracorporeal anastomosis (IA) may improve outcomes compared with extracorporeal anastomosis (EA) in minimally invasive right colectomy. This is a pr...

Feasibility study to improve deep learning in OCT diagnosis of rare retinal diseases with few-shot classification.

Deep learning (DL) has been successfully applied to the diagnosis of ophthalmic diseases. However, rare diseases are commonly neglected due to insuffi...

Risk of Upper-body Adverse Events in Robot-assisted Total Laparoscopic Hysterectomy for Benign Gynecologic Disease.

STUDY OBJECTIVE: Recent studies suggest that prolonged Trendelenburg positioning during robot-assisted total laparoscopic hysterectomy (RA-TLH) may le...

Machine-Learning Provides Patient-Specific Prediction of Metastatic Risk Based on Innovative, Mechanobiology Assay.

Cancer mortality is mostly related to metastasis. Metastasis is currently prognosed via histopathology, disease-statistics, or genetics; those are pot...

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The field of Medicine and Healthcare has attained revolutionary advancements in the last forty years. Within this period, the actual reasons behind nu...

Evaluation and development of deep neural networks for image super-resolution in optical microscopy.

Deep neural networks have enabled astonishing transformations from low-resolution (LR) to super-resolved images. However, whether, and under what imag...

Sarcoma classification by DNA methylation profiling.

Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class o...

Manipulation of Single Neural Stem Cells and Neurons in Brain Slices using Robotic Microinjection.

A central question in developmental neurobiology is how neural stem and progenitor cells form the brain. To answer this question, one needs to label, ...

The 3D reconstructed skin micronucleus assay using imaging flow cytometry and deep learning: A proof-of-principle investigation.

The reconstructed skin micronucleus (RSMN) assay was developed in 2006, as an in vitro alternative for genotoxicity evaluation of dermally applied che...

Flexible and Expandable Robot for Tissue Therapies - Modeling and Design.

OBJECTIVE: Implantable technologies should be mechanically compliant with the tissue in order to maximize tissue quality and reduce inflammation durin...

Robust Mosaicing of Endomicroscopic Videos via Context-Weighted Correlation Ratio.

Probe-based confocal laser endomicroscopy (pCLE) is a promising imaging tool that provides in situ and in vivo optical imaging to perform real-time pa...

Bi-channel image registration and deep-learning segmentation (BIRDS) for efficient, versatile 3D mapping of mouse brain.

We have developed an open-source software called bi-channel image registration and deep-learning segmentation (BIRDS) for the mapping and analysis of ...

Artificial intelligence and computational pathology.

Data processing and learning has become a spearhead for the advancement of medicine, with pathology and laboratory medicine has no exception. The inco...

Classification of malignant tumours in breast ultrasound using unsupervised machine learning approaches.

Traditional computer-aided diagnosis (CAD) processes include feature extraction, selection, and classification. Effective feature extraction in CAD is...

Automated Extraction of Skin Wound Healing Biomarkers From In Vivo Label-Free Multiphoton Microscopy Using Convolutional Neural Networks.

BACKGROUND AND OBJECTIVES: Histological analysis is a gold standard technique for studying impaired skin wound healing. Label-free multiphoton microsc...